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Metro mid-senior data role with broad Azure/Databricks skills and known enterprise brand.
Data engineering skills are broadly transferable, but enterprise Azure/Databricks experience favors similar industries.
Explicit 6–8+ years requirement plus mandatory Azure, Databricks, SQL/Python skills increases filter strictness.
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Design and develop scalable, real-time data pipelines using Azure services to support autonomous AI systems.
Build and maintain enterprise-scale ETL/ELT workflows for both structured and unstructured data while ensuring data quality, security, and compliance.
Optimize data processing for performance and cost, implement CI/CD pipelines, and collaborate cross-functionally to support analytics, reporting, and machine learning initiatives.
6–8+ years of experience in Data Engineering.
Minimum 3+ years of hands-on experience with Microsoft Azure data services.
Strong proficiency in SQL and Python; experience with ETL/ELT solution development.
Familiarity with Azure Data Factory, Azure Databricks, Azure SQL Database, and related Azure technologies.
Experienced in building and optimizing scalable, real-time data infrastructure on Azure cloud, aligned with AI-driven enterprise environments.
Deep technical skills in Azure ecosystem combined with programming expertise in Python, SQL, PySpark, and basic Java knowledge.
Capable of developing reusable frameworks and adhering to best practices for high data quality, governance, and operational efficiency in large organizations.